1. Field of the Invention
This invention relates generally to the circuit structure and method for digital signal and image data processing. More particularly, this invention relates to the circuit structure, system configurations and the methods for applying a pseudo four-point interpolation (PFPI) to digital signal and image data processing.
2. Description of the Prior Art
As there are greater demand for higher quality image display or high fidelity audio recording and broadcasting, the performance levels of such systems are often dictated by the speed and accuracy of sampled data processing, such as data interpolation. Particularly, due to the demands for higher quality output from these systems, the sampling rates as originally provided as input often become insufficient to satisfy the accuracy or quality requirements. A method of interpolation is often employed to generate more data points between the sampled data for the purpose of improving the quality of system output. One of the most common applications is for a graphic display system to zoom up a particular zone of the display field wherein more display data must be generated instantaneously at high speed and with high precision such that the zoom-image can be produced on demand and without distortions.
FIG. 1 shows the method employed by a conventional interpolation scheme wherein a typical two-point linear interpolation algorithm is applied. In order to obtain an interpolated point between two sampled data f.sub.i-1 and f.sub.i, an assumption is made that there is a first order linear function exists between these two sampled data, i.e., f.sub.i-1 and f.sub.i. On the basis of this simple assumption, a straight line is connected between f.sub.i-1 and f.sub.i. A new interpolated sample point f can therefore be computed by simply providing the relative position of this interpolated sample point f. Generally, this relative position of f is provided as a ratio of distances between the point f to f.sub.i-1 and point f.sub.i to f.sub.i-1.
The conventional interpolation technique presents two problems. First, this simple assumption of a first order liner function between two sampled point is often not sufficiently accurate. This is especially true where there are greater variations between two sampled points. For example, in an image display field, the light intensity between two pixels on the edges of a display subject generally has a sudden and non-linear variations. This conventional simple model will not be able to provide high quality definition of the edges for the subject when a zooming image is required. Secondly, due to this limitation in accuracy, the conventional two-point technique is not able to consistently generate high quality zooming images which is often required in modern image processing devices. When a targeted small area of an image field is zoomed, the display data of additional image pixels must be calculated and then inserted for display. These processes have to be performed instantaneously. The quality of the zooming images are often limited by the greater distortions of the interpolated image pixels. Particularly, display image may become distorted for a zooming operation performed in an area where greater data-variations are present between adjacent pixels in the original image field. The zooming function of a video device is degraded due to the unpleasant visual effects cause by the distorted interpolation computations employed in the conventional video systems.
For the purpose of improving the interpolation accuracy, various techniques have been proposed. More sampled data points may be used for the computation of an interpolated point. These techniques often involve the use of quadratic or even higher order functions as approximations for providing a correlation between the multiple sampled data points and the intended interpolated point. However, because the solution process of these higher order functions often involve more complex computations, the processing speed usually is significantly decreased. Therefore, even that the techniques of employing more sampled points by solving higher order equations can provide higher interpolation accuracy and better quality interpolated results, the slower processing speed nevertheless often becomes the greatest limitation. The usefulness of these techniques are still very restricted.
Therefore, there is still a demand in the art of digital signal processing for an improved interpolation technique. Particularly, in the fields of the audio, visual or other multimedia applications where sampled data interpolation techniques are constantly being employed, it is critically important to have an interpolation technique which can provide accurate interpolation data and in meantime satisfying the high speed processing requirement. Therefore, it is required that this interpolation process can be effectively executed at high speed without the need of using complex algorithms. Preferably, this interpolation technique can be implemented by the use of modularized circuit structures such that the implementation can be carried out conveniently and economically.